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Ovarian clear cell carcinoma (CCC) has an East Asian preponderance. It is associated with endometriosis, a benign condition where endometrial (inner lining of the uterus) tissue is found outside the uterus and on the peritoneal surface, in the abdominal or pelvic space. CCC is relatively more resistant to conventional chemotherapy compared to other ovarian cancer subtypes and is associated with a poorer prognosis. In this study, we recruited and obtained tumour tissues from seven patients across the four stages of CCC. The tumour and the tumour microenvironment (TME) from 7 CCC patients spanning clinical stages 1-4 were transcriptionally profiled using high-resolution scRNA-seq to gain insight into CCC's biological mechanisms. Firstly, we built a scRNA-seq resource for the CCC tumour microenvironment (TME). Secondly, we identified the different cell type proportions and found high levels of immune infiltration in CCC. Thirdly, since CCC is associated with endometriosis, we compared CCC with two publicly available endometriosis scRNA-seq datasets. The CCC malignant cells showed similarities with glandular secretory and ciliated epithelial cells found in endometriosis. Finally, we determined the differences in cell-cell communication between various cell types present in CCC TME and endometriosis conditions to gain insights into the transformations in CCC., Competing Interests: Conflict of interest statement None declared.

Motivation: As the generation of complex single-cell RNA sequencing datasets becomes more commonplace it is the responsibility of researchers to provide access to these data in a way that can be easily explored and shared. Whilst it is often the case that data is deposited for future bioinformatic analysis many studies do not release their data in a way that is easy to explore by non-computational researchers., Results: In order to help address this we have developed ShinyCell, an R package that converts single-cell RNA sequencing datasets into explorable and shareable interactive interfaces. These interfaces can be easily customized in order to maximize their usability and can be easily uploaded to online platforms to facilitate wider access to published data., Availability and Implementation: ShinyCell is available at https://github.com/SGDDNB/ShinyCell and https://figshare.com/projects/ShinyCell/100439., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The need to derive and culture diverse cell or tissue types in vitro has prompted investigations on how changes in culture conditions affect cell states. However, the identification of the optimal conditions (e.g., signaling molecules and growth factors) required to maintain cell types or convert between cell types remains a time-consuming task. Here, we developed EpiMogrify, an approach that leverages data from ∼100 human cell/tissue types available from ENCODE and Roadmap Epigenomics consortia to predict signaling molecules and factors that can either maintain cell identity or enhance directed differentiation (or cell conversion). EpiMogrify integrates protein-protein interaction network information with a model of the cell's epigenetic landscape based on H3K4me3 histone modifications. Using EpiMogrify-predicted factors for maintenance conditions, we were able to better potentiate the maintenance of astrocytes and cardiomyocytes in vitro. We report a significant increase in the efficiency of astrocyte and cardiomyocyte differentiation using EpiMogrify-predicted factors for conversion conditions., Competing Interests: Declaration of Interests O.J.L.R., E.P., U.S.K., J.M.P., and J.C. have filed a patent (PCT application no: PCT/AU, 2020/050656 titled “Cell Culture Methods and Compositions” filed on June 26, 2020). There are restrictions to the availability of some predicted culture conditions and EpiMogrify code, as they are subject to the patent application and are under commercial investigation. O.J.L.R. and J.M.P. are also co-inventors of the patent (WO/2017/106932) and are co-founders, scientific advisory board members, and shareholders of Mogrify Ltd, a cell therapy company. All other authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Next-generation sequencing (NGS) techniques offer an unprecedented "step-change" increase in the quantity and quality of sequence data rapidly generated from a sample and can be applied to obtain ultra-deep coverage of viral genomes. This is not possible with the routinely used Sanger sequencing method that gives the consensus reads, or by cloning approaches. In this study, a targeted-enrichment methodology for the simultaneous acquisition of complete foot-and-mouth disease virus (FMDV) genomes directly from clinical samples is presented. Biotinylated oligonucleotide probes (120 nt) were used to capture and enrich viral RNA following library preparation. To create a virus capture panel targeting serotype O and A simultaneously, 18 baits targeting the highly conserved regions of the 8.3 kb FMDV genome were synthesised, with 14 common to both serotypes, 2 specific to serotype O and 2 specific to serotype A. These baits were used to capture and enrich FMDV RNA (as cDNA) from samples collected during one pathogenesis and two vaccine efficacy trials, where pigs were infected with serotype O or A viruses. After enrichment, FMDV-specific sequencing reads increased by almost 3000-fold. The sequence data were used in variant call analysis to identify single nucleotide polymorphisms (SNPs). This methodology was robust in its ability to capture diverse sequences, was shown to be highly sensitive, and can be easily scaled for large-scale epidemiological studies., (Crown Copyright © 2019. Published by Elsevier B.V. All rights reserved.)

The frequency of epidemics caused by Dengue viruses 1-4, Zika virus and Chikungunya viruses have been on an upward trend in recent years driven primarily by uncontrolled urbanization, mobility of human populations and geographical spread of their shared vectors, Aedes aegypti and Aedes albopictus. Infections by these viruses present with similar clinical manifestations making them challenging to diagnose; this is especially difficult in regions of the world hyperendemic for these viruses. In this study, we present a targeted-enrichment methodology to simultaneously sequence the complete viral genomes for each of these viruses directly from clinical samples. Additionally, we have also developed a customized computational tool (BaitMaker) to design these enrichment baits. This methodology is robust in its ability to capture diverse sequences and is amenable to large-scale epidemiological studies. We have applied this methodology to two large cohorts: a febrile study based in Colombo, Sri Lanka taken during the 2009-2015 dengue epidemic (n = 170) and another taken during the 2016 outbreak of Zika virus in Singapore (n = 162). Results from these studies indicate that we were able to cover an average of 97.04% ± 0.67% of the full viral genome from samples in these cohorts. We also show detection of one DENV3/ZIKV co-infected patient where we recovered full genomes for both viruses., Competing Interests: The authors have declared that no competing interests exist.

This chapter was published without including the "Conflict of Interest" section given by the author along with the corrected proof.

The process of identifying sets of transcription factors that can induce a cell conversion can be time-consuming and expensive. To help alleviate this, a number of computational tools have been developed which integrate gene expression data with molecular interaction networks in order to predict these factors. One such approach is Mogrify, an algorithm which ranks transcriptions factors based on their regulatory influence in different cell types and tissues. These ranks are then used to identify a nonredundant set of transcription factors to promote cell conversion between any two cell types/tissues. Here we summarize the important concepts and data sources that were used in the implementation of this approach. Furthermore, we describe how the associated web resource ( www.mogrify.net ) can be used to tailor predictions to specific experimental scenarios, for instance, limiting the set of possible transcription factors and including domain knowledge. Finally, we describe important considerations for the effective selection of reprogramming factors. We envision that such data-driven approaches will become commonplace in the field, rapidly accelerating the progress in stem cell biology.

Influenza A and B viruses are the causative agents of annual influenza epidemics that can be severe, and influenza A viruses intermittently cause pandemics. Sequence information from influenza virus genomes is instrumental in determining mechanisms underpinning antigenic evolution and antiviral resistance. However, due to sequence diversity and the dynamics of influenza virus evolution, rapid and high-throughput sequencing of influenza viruses remains a challenge. We developed a single-reaction influenza A/B virus (FluA/B) multiplex reverse transcription-PCR (RT-PCR) method that amplifies the most critical genomic segments (hemagglutinin [HA], neuraminidase [NA], and matrix [M]) of seasonal influenza A and B viruses for next-generation sequencing, regardless of viral type, subtype, or lineage. Herein, we demonstrate that the strategy is highly sensitive and robust. The strategy was validated on thousands of seasonal influenza A and B virus-positive specimens using multiple next-generation sequencing platforms., (Copyright © 2017 American Society for Microbiology.)

Directed cell conversion (or transdifferentiation) of one somatic cell-type to another can be achieved by ectopic expression of a set of transcription factors. Since the experimental identification of transcription factors for transdifferentiation is extremely time-consuming and expensive, there are still relatively few transdifferentiations achieved in comparison to the number of human cell-types. However, the growing volume of transcriptional data available and the recent introduction of data-driven algorithmic approaches that predict factors for transdifferentiation holds great promise for accelerating this field. Here we review those computational methods whose in-silico predictions have been experimentally validated, highlighting differences and similarities. Our analysis reveals that the factors predicted by each method tend to be different due to varying source cells used, gene expression quantification and algorithmic steps. We show these differences have an impact on the regulatory influences downstream, with some methods favoring transcription factors regulating developmental progression and others favoring factors regulating mature cell processes. These computational approaches offer a starting point to predict and test novel factors for transdifferentiation. We argue that collecting high-quality gene expression data from single-cells or pure cell-populations across a broader set of cell-types would be necessary to improve the quality and consistency of the in-silico predictions.

Unlabelled: CELADEN was a randomized placebo-controlled trial of 50 patients with confirmed dengue fever to evaluate the efficacy and safety of celgosivir (A study registered at ClinicalTrials.gov, number NCT01619969). Celgosivir was given as a 400 mg loading dose and 200 mg bid (twice a day) over 5 days. Replication competent virus was measured by plaque assay and compared to reverse transcription quantitative PCR (qPCR) of viral RNA. Pharmacokinetics (PK) correlations with viremia, immunological profiling, next generation sequence (NGS) analysis and hematological data were evaluated as exploratory endpoints here to identify possible signals of pharmacological activity. Viremia by plaque assay strongly correlated with qPCR during the first four days. Immunological profiling demonstrated a qualitative shift in T helper cell profile during the course of infection. NGS analysis did not reveal any prominent signature that could be associated with drug treatment; however the phylogenetic spread of patients' isolates underlines the importance of strain variability that may potentially confound interpretation of dengue drug trials conducted during different outbreaks and in different countries. Celgosivir rapidly converted to castanospermine (Cast) with mean peak and trough concentrations of 5727 ng/mL (30.2 μM) and 430 ng/mL (2.3 μM), respectively and cleared with a half-life of 2.5 (± 0.6) hr. Mean viral log reduction between day 2 and 4 (VLR2-4) was significantly greater in secondary dengue than primary dengue (p = 0.002). VLR2-4 did not correlate with drug AUC but showed a trend of greater response with increasing Cmin. PK modeling identified dosing regimens predicted to achieve 2.4 to 4.5 times higher Cmin. than in the CELADEN trial for only 13% to 33% increase in overall dose. A small, non-statistical trend towards better outcome on platelet nadir and difference between maximum and minimum hematocrit was observed in celgosivir-treated patients with secondary dengue infection. Optimization of the dosing regimen and patient stratification may enhance the ability of a clinical trial to demonstrate celgosivir activity in treating dengue fever based on hematological endpoints. A new clinical trial with a revised dosing regimen is slated to start in 2016 (NCT02569827). Furthermore celgosivir's potential value for treatment of other flaviruses such as Zika virus should be investigated urgently., Trial Registration: ClinicalTrials.gov NCT01619969.

The development of live viral vaccines relies on empirically derived phenotypic criteria, especially small plaque sizes, to indicate attenuation. However, while some candidate vaccines successfully translated into licensed applications, others have failed safety trials, placing vaccine development on a hit-or-miss trajectory. We examined the determinants of small plaque phenotype in two dengue virus (DENV) vaccine candidates, DENV-3 PGMK30FRhL3, which produced acute febrile illness in vaccine recipients, and DENV-2 PDK53, which has a good clinical safety profile. The reasons behind the failure of PGMK30FRhL3 during phase 1 clinical trial, despite meeting the empirically derived criteria of attenuation, have never been systematically investigated. Using in vitro, in vivo and functional genomics approaches, we examined infections by the vaccine and wild-type DENVs, in order to ascertain the different determinants of plaque size. We show that PGMK30FRhL3 produces small plaques on BHK-21 cells due to its slow in vitro growth rate. In contrast, PDK53 replicates rapidly, but is unable to evade antiviral responses that constrain its spread hence also giving rise to small plaques. Therefore, at least two different molecular mechanisms govern the plaque phenotype; determining which mechanism operates to constrain plaque size may be more informative on the safety of live-attenuated vaccines.

Despite Japan's temperate climate, a dengue outbreak occurred in Tokyo for the first time in over 70 years in 2014. We dissected this dengue outbreak based on phylogenetic analysis, travel interconnectivity, and environmental drivers for dengue epidemics. Comparing the available dengue virus 1 (DENV1) E gene sequence from this outbreak with 3,282 unique DENV1 sequences in National Center for Biotechnology Information suggested that the DENV might have been imported from China, Indonesia, Singapore, or Vietnam. With travelers arriving into Japan, Guangzhou (China) may have been the source of DENV introduction, given that Guangzhou also reported a large-scale dengue outbreak in 2014. Coinciding with the 2014 outbreak, Tokyo's climate conditions permitted the amplification of Aedes vectors and the annual peak of vectorial capacity. Given suitable vectors and climate conditions in addition to increasing interconnectivity with endemic areas of Asia, Tokyo's 2014 outbreak did not come as a surprise and may foretell more to come., (© The American Society of Tropical Medicine and Hygiene.)

Dengue viruses (DENV) cause debilitating and potentially life-threatening acute disease throughout the tropical world. While drug development efforts are underway, there are concerns that resistant strains will emerge rapidly. Indeed, antiviral drugs that target even conserved regions in other RNA viruses lose efficacy over time as the virus mutates. Here, we sought to determine if there are regions in the DENV genome that are not only evolutionarily conserved but genetically constrained in their ability to mutate and could hence serve as better antiviral targets. High-throughput sequencing of DENV-1 genome directly from twelve, paired dengue patients' sera and then passaging these sera into the two primary mosquito vectors showed consistent and distinct sequence changes during infection. In particular, two residues in the NS5 protein coding sequence appear to be specifically acquired during infection in Ae. aegypti but not Ae. albopictus. Importantly, we identified a region within the NS3 protein coding sequence that is refractory to mutation during human and mosquito infection. Collectively, these findings provide fresh insights into antiviral targets and could serve as an approach to defining evolutionarily constrained regions for therapeutic targeting in other RNA viruses.